IBM Almaden Research Center, San Jose, California.
J Am Coll Radiol. 2018 Mar;15(3 Pt B):569-576. doi: 10.1016/j.jacr.2018.01.028.
The field of diagnostic decision support in radiology is undergoing rapid transformation with the availability of large amounts of patient data and the development of new artificial intelligence methods of machine learning such as deep learning. They hold the promise of providing imaging specialists with tools for improving the accuracy and efficiency of diagnosis and treatment. In this article, we will describe the growth of this field for radiology and outline general trends highlighting progress in the field of diagnostic decision support from the early days of rule-based expert systems to cognitive assistants of the modern era.
放射诊断决策支持领域正随着大量患者数据的出现以及深度学习等新型人工智能机器学习方法的发展而发生快速变革。它们有望为影像专家提供工具，以提高诊断和治疗的准确性和效率。本文将描述放射学领域这一领域的发展，并概述一般趋势，重点介绍从基于规则的专家系统早期到现代认知助手的诊断决策支持领域的进展。
